DCAgent/g1_min_episodes_e1_gpt_long_tacc
DCAgent/g1_min_episodes_e1_gpt_long_tacc is an 8 billion parameter language model, fine-tuned from Qwen/Qwen3-8B. This model is specifically adapted using the DCAgent/g1_min_episodes_e1_gpt_long_d1_original_40k_glm47_traces dataset. It is designed for tasks related to its specific fine-tuning data, offering specialized performance within that domain.
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Overview
This model, sft__g1_min_episodes_e1_gpt_long_d1_original_40k_glm47_traces__Qwen3-8B, is an 8 billion parameter language model. It is a fine-tuned variant of the base model Qwen/Qwen3-8B.
Key Characteristics
- Base Model: Qwen3-8B architecture.
- Fine-tuning Dataset: Specialized on the
DCAgent/g1_min_episodes_e1_gpt_long_d1_original_40k_glm47_tracesdataset. - Training Hyperparameters:
- Learning Rate: 4e-05
- Optimizer: AdamW_Torch_Fused
- Epochs: 7.0
- Distributed Training: Multi-GPU with 16 devices.
Intended Use Cases
Given its fine-tuning on a specific dataset, this model is best suited for applications and research that align with the characteristics and domain of the DCAgent/g1_min_episodes_e1_gpt_long_d1_original_40k_glm47_traces data. Developers should consider its specialized training for tasks requiring nuanced understanding or generation within that particular context.
Limitations
Specific limitations are not detailed in the provided information, but as a fine-tuned model, its performance may be highly dependent on the similarity between the target use case and its training data. Generalization to vastly different domains might be limited.